The broad goal of this project is to create a publicly accessible naturalistic driving database, using novel methods to identify unsafe driving events, with the expectation that this methodology could also be adapted for more widespread clinical and experimental use. This project will leverage the wealth of knowledge and experience that has been gained from two previous projects examining real-world driving in normal aging and dementia, one employing serial road tests in a 3-year longitudinal study, the other involving naturalistic recordings of drivers with in-car video cameras studied over one year. We will use the large volume of baseline and one-year follow up digital video collection of naturalistic drivin from the second study (N=103), NIA 2R01 #AG016335, Naturalistic assessment of driving in cognitively impaired elders, which could not be manually reviewed completely. The data will be re-analyzed in totality using new and highly innovative methods of computerized analysis of lane deviation and near miss events, and then scored by safety rating methods. This research project will also include secondary analyses of naturalistic driving data on older drivers with and without cognitive impairment comparing naturalistic driving to prior history of motor vehicle accidents and road test scores. The resulting bookmarked video and tabular data, including demographic, road test, and cognitive test information, will be a valuable naturalistic driving resource that will be archived and disseminated for other researchers to use in their own studies of older drivers. We will disseminate the archived naturalistic data through the National Archive of Computerized Data on Aging (NACDA) as well as notify the public of data availability on the research teams' websites and publications of secondary analyses. By proper and thorough de-identification of the video recordings, this data archive will facilitate the use of data that woul otherwise not be available due to the difficulty in obtaining such data as well as the sensitive nature of the data obtained.